Browsing by Author "Windapo, Abimbola Olukemi"

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    Open Access
    An evaluation of the contextual factors that affect labour productivity in the South African Construction Industry
    (2019) Lefoka, Mochelo Mackson; Windapo, Abimbola Olukemi
    Poor labour productivity is an endemic global problem in the construction industry. In the past two decades, it has been observed over the different sectors of the construction industry that the labour productivity expended on projects has reported a decline, particularly in the building and civil sectors. This research explores the variables that affect labour productivity on construction sites and whether the estimation practices used considers the various circumstances in which buildings and infrastructure are produced. Literature review aided in the identification of contextual factors classified in four categories that affect labour productivity on construction projects. These categories were; site environment factors, organisational factors, technical factors and social factors. These factors were used in the development and design of the questionnaire to analyse the impact of these factors on construction labour productivity. The population of the study comprised of directors, contracts managers, project and construction managers, quantity surveyors and estimators who are employees of construction firms listed in Grades 2-9 of the Construction Industry Development Board (cidb) Register of Contractors in South Africa. The study area covered nine provinces of South Africa. At the end of the survey period, 117 valid responses were received and analysed. The findings of the study revealed that at the pre-construction phase of a construction project, social factors, complexity of the project and organisational factors are not considered in the estimation practices and techniques. Results further revealed that four core factors that affect productivity of labour are; lack of experience amongst workers, delays in the wages of labourers, change orders from designers/consultants and the relationships between labourers and their supervisors. The study established a relationship between the contextual factors and labour productivity on construction projects. Motivation and training emerged as significant changes needed to improve labour productivity on projects. Based on these findings, the study concludes that labour productivity is impacted by contextual site factors such as lack of experience, delays in labour payment and that these are not considered by estimators at the project pre-construction phase. The study recommends that these site factors need to be considered during the preconstruction phase of a project in order to allow for their impact on labour productivity during construction. Furthermore, a benchmark and standard of what constitutes effective labour productivity needs to be developed on construction sites, especially one that is project specific and considering all the four categories of contextual factors and their probable impacts.
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    An Investigation of the Utilisation and Barriers to the Social Acceptance of Alternative Building Technology in Housing Construction in South Africa
    (2022) Adetooto, Johnson Damilola; Windapo, Abimbola Olukemi
    Social acceptance and the adoption of Alternative Building Technology (ABT), with a focus on Sandbag Building Technology (SBT) in housing delivery, are imperative to bridging the ever increasing deficit in housing provision in South Africa, which stands at about 2.2 million units. However, ABT's adoption is influenced by issues, and its promotion is a difficult task in South Africa. This dissertation investigates the extent of use and the barrier to the social acceptance of ABT, focusing on SBT in housing construction in South Africa. It develops a framework to promote the social acceptability of ABT in housing delivery in South Africa. Specifically, this study has five objectives: (1) to determine the actor's perceptions of SBT as a sustainable and affordable housing solution in South Africa; (2) to identify and establish the critical drivers of social acceptance of SBT in South Africa; (3) to identify and establish the concomitant impediment to the social acceptance of SBT in South Africa; (4) to identify and establish the major strategies for the social acceptance of SBT in South Africa, and (5) to develop a framework for the uptake and social acceptance of SBT in South Africa. The objectives were achieved through a mixed research method that began with two focus group sessions with thirteen (13) randomly selected South African housing market players and end-users. Also, a questionnaire survey was conducted across South Africa's nine provinces and yielded 228 valid responses. The data were analysed using various methods such as inductive content analysis with NVivo, the Shapiro-Wilk test and Cronbach's Alpha, a mean score rating, the Kruskal-Wallis H Test, the Kaiser-Meyer-Olkin (KMO) sample adequacy measure and Bartlett's sphericity, and factor analysis. The hypotheses developed for the study were tested using the Partial least squares structural equation modelling (PLS-SEM) analysis technique. The findings revealed that the government-investor-related barrier, comprised of the government's lack of promotion of sandbags, their lack of interest and lack of finance schemes (bank loans, grants), is significant in impeding the social acceptance and use of SBT in South Africa. The study revealed that to promote the social acceptance of SBT there is a need for stakeholder integration; and that the government and the other South African housing market players need to support the adoption of SBT through the formation of strategic policy. More so, there is a need for effective education, training, availability of sandbag demonstration projects in all provinces, and knowledge sharing among South African housing stakeholders and end-users. The major benefits of SBT, which include its economic, construction and health- related benefits, should be communicated to South African housing stakeholders and the general public to promote its acceptance. This study provides a comprehensive framework for the social acceptance and adoption of sandbag technology in housing projects by drawing on the diverse opinions and practical experience of ABT experts and housing industry stakeholders in South Africa. In addition, this is the first and only effort to establish a framework for effectively adopting sandbag technology in South Africa, to provide inexpensive and sustainable housing. If completely implemented and approved, the framework will contribute to resolving South Africa's housing shortfall problem. Furthermore, the findings can be used as a policy tool and useful guidelines for government agencies, international organisations, and advocates interested in promoting a variety of ABTs such as sandbags in South Africa, to achieve more sustainable and affordable housing delivery.
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    Developing a leadership framework for improving construction business organisation performance in South Africa
    (2022) Alade, Kehinde Temitope; Windapo, Abimbola Olukemi
    The South African construction industry is experiencing challenging times, like its counterparts globally, which has led to the failure of known large contractors. While some studies have suggested different reasons for this, a stream of scholars argued that company leadership contributes significantly to the organisation's performance. Studies on leadership in construction have mainly been undertaken at project level, considering that construction organisations are project-based. This study examined the leadership of construction organisations and whether the traits, skills, role, style and strategic decisions of company leaders impacted on the long-term performance and sustainability of contracting firms in South Africa. The main question investigated in this study is: what combination of leadership traits, skills, style, role, and strategic decisions results in superior and sustainable construction organisation performance, when moderated by strategic decisions of CEO/company leadership? The study draws from theoretical perspectives, namely the ‘upper echelons' theory, strategic leadership theory, and the Full Range Leadership Model (FRLM), to develop a conceptual framework. A convergent mixed-method research design was used to advance the investigation. Fifteen semi-structured interviews were conducted with purposively selected construction company leaders of large contracting firms in the Western Cape, in positions of Group Chairman, Chief Executive Officer (CEO) or Managing Director in major building construction, civil engineering, or geo-technical companies of good repute. The survey instrument was pretested by construction company leaders before distribution to respondents and the Crobach Alpha test was used in testing the reliability of the study responses. The cidb provided the database of the construction leaders and a survey of contractors listed in Grades 7-9 of the cidb Register of Contractors was conducted. The responses of the samples on the survey question raised on their position also attests to this. At the end of the survey period between April and September 2020, 257 responses were received, representing 56.86% response rate. The data collected were analysed using descriptive and inferential statistics, including Structural Equation Modeling (SEM), to validate the hypothesis developed that construction company leaders positively impact organisational performance through their strategic decisions on project management, change, and innovation and investment. In addition, the study also tested the hypothesis that strategic decisions mediate the relationship between construction companies' leadership components, characteristics, and construction organisation performance. The findings of this study reveal that decisions on change and innovation have the most impact to prevent business failure, and for construction organisation performance. Whilst there are other internal and external factors that may contribute to a firm's business outcomes, the findings of the study explain that the attributes of construction business leaders and their strategic decisions play a significant role in construction company leadership and construction organisation's outcomes. The leadership of construction companies is expected to be exhibit transformational qualities, cast visions, channel new opportunities, and reposition their companies according to the current and future economic situations. The gap between expectations and performance must thus be filled by leadership through their strategic decisions that are premeditated and calculated towards the expectations and visions of the construction companies. The study thus contributes to knowledge in leadership and construction research by demonstrating how the multi-dimensions of company leadership impact construction business organisation performance. The integration of leadership personality traits, skills, style, role, and strategic decisions provides a better measure of how leadership impacts organisational performance. The leadership framework developed from the study's findings made explicit the leadership traits, skills, style and strategic roles that would assist construction company leaders to operate their organisations sustainably and devise effective succession plans. The components of the leadership framework include the strategic leadership roles that construction organisational leaders must play, using catalytic leadership skills, transformational and transactional leadership approaches and inherent leadership traits, which could be developed through education, career experiences, mentoring and training. The study is limited to South Africa, which has implications for the generalisability of results.
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    Diversification and dynamic capabilities within construction business models and their impact on firm performance
    (2024) Filtane, Amanda Alicia; Windapo, Abimbola Olukemi
    This study focuses on the levels of diversity within construction business models and their impact on business performance. This study examines the impact of diversification and dynamic capabilities on firm performance in the South African construction industry. The author's findings indicate a statistically significant relationship between the international diversification of construction business portfolios and both the diversification of the construction sector and the allocation of resources within construction organisations. A significant correlation exists between physical and human resources and the diversification of the construction sector. The findings provide evidence and validation for the theory of dynamic capabilities as influential factors in the value creation of construction organisations. Additionally, the study highlights the significance of both physical and human resources in ensuring the optimal performance of construction organisations. A study strategy known as "mixed methods" was used, which consisted of employing both quantitative and qualitative approaches for data collection and analysis. Survey data were collected as well as case study firms identified through rigorous qualification criteria, where further detailed observations were made and firm performance data spanning over 5 financial years were analysed and findings discussed. In summary, this doctoral thesis contributes significantly to the advancement of our understanding of construction business models and their impact on organisational performance in South Africa. The research findings presented in this study offer significant insights for both academic researchers and industry practitioners in the construction sector, regarding the interrelationships among international diversification, resource allocation, and dynamic capabilities. In addition, the study developed a programmable coded construction business model framework that enables a more comprehensive examination of construction business models and their resulting performance outcomes. Construction companies can thus make informed decisions and develop strategies to navigate a complex and changing business environment.
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    Evaluation of building information modelling (BIM) adoption, capability and maturity within South African consulting and construction firms
    (2019) Mtya, Amanda; Windapo, Abimbola Olukemi
    The Construction Industry Indicators (CIIs) continue to reflect a steady growth in the level of client dissatisfaction with the performance of contractors and consultants on construction projects whilst firms in the industry battle for survival. In order to survive in the highly competitive construction market, firms within the industry, need a paradigm shift. To move from traditional project delivery methodologies which continue to yield unsatisfactory results to innovative project delivery methods and practices. With the advancements in computational technologies and processes, the industry needs to move towards integrated, collaborative and computable processes, to increase productivity, efficiency, infrastructure value, quality and sustainability, reduce lifecycle costs, lead times and duplications. Building Information Modelling (BIM) is the innovative project delivery method that helps reduce fragmentation and provides opportunities for enhanced collaboration and distributed project development. BIM is slowly gaining momentum in the South African construction industry. Even though there is an abundance of industry discussions and academic literature professing the ability of BIM methodologies to increase productivity, scholars have found that it has not yet been coupled with the availability of useful metrics, knowledge and tools to reliably measure BIM benefits. Few organisations and individuals have been exposed to some BIM tools whilst many still lack thorough understanding of BIM as a project delivery method. To capture the full benefit of BIM methodologies, firms in project networks must coordinate and develop interoperable business practices and procedures. This study assessed the level of BIM adoption, capability and maturity in consulting and construction firms and evaluated if there were differences in the level of adoption, capability and maturity of BIM between consulting and construction firms. The study also evaluated the relationship between level of BIM maturity and project performance of consulting and construction firms. The study found that there is a statistically significant relationship between the level of BIM capability and project performance. Lastly, the study reports on the current perceived benefits of BIM in the South African construction industry.
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    Modelling cost and time performance of public building projects in a terror impacted area of Nigeria
    (2019) Oboirien, Momoh Ohiomah; Windapo, Abimbola Olukemi; Odeyinka, Henry Agboola
    Examine the impact of construction cost-and-time-influencing factors on the production performance of public building projects in north eastern Nigeria and whether a predictive model could be devised in assessing this impact. The global poor performances of construction project cost and time, coupled with a dearth of studies into using machine learning systems as artificial neural networks for advanced cost and time impact predictions, has made researching into construction project performance imperative. Moreover, the Boko Haram insurgency in Nigeria's North East geopolitical zone intensified the disruptions of construction site programmes with consequent cost increases. Therefore, prediction and performance measurement tools for construction project cost and time can possibly be developed from the examination of data on initial contract sums, estimated construction duration, final cost, actual construction duration, and the influence of cost and time driving factors on public building projects in north eastern Nigeria. The research objectives include an assessment of the factors influencing the cost and time performance of public building projects in north eastern Nigeria and determination of the cost and time performance of selected public building projects in the study area. Others are the development of models for assessing the impact of cost and time influencing factors on the performance of cost and time in public building projects in the study area. Lastly validation of the developed cost and time performance impact assessment models of public building projects in the study area. A quantitative research approach that employs a questionnaire survey was adopted in sourcing primary and secondary data from purposively sampled construction industry professionals. The study used one-way between-groups Analysis of Variance with a post-hoc test, one-way repeated measures Analysis of Variance with Wilks’ lambda tests, multiple linear regressions (MLR), Factor analysis (FA), and Artificial Neural Network (ANN) to analyze the data collected. This data was about initial contract sums, estimated construction duration, final cost, actual construction duration, and the influence of the identified driving factors on public building projects, completed between 2012 and 2017. The study found that the mean percentage cost overrun of the projects studied decreases from uncomplicated projects to moderately complex projects; and increases from moderately complex to largely complex projects. Also, the mean percentage time overrun decreases with increases in project complexity. The significant cost influencing factors are the inexperience of the contract manager, payment delays to main contractors, unstable foreign exchange, variations to works, and corrupt practices. The time influencing factors include design errors, cash flow problems, payment delays to main contractors, contractors’ improper contract knowledge, and delay in building plans and approval. These factors found in the study area were used to develop MLR and ANN cost and time impact prediction models. The developed ANN impact prediction models were validated and compared using previous similar studies in terms of relative absolute deviations and mean absolute percentage errors. The MLR models, although better than the ANNs in terms of mean absolute percentage errors and relative mean absolute deviations, it yeilded poor explanations of the variances in the dependent variables (impacts or overruns) by the independent variables (multiple influence factors). The alternative ANN impact prediction models’ statistics are: (i) MAPE of the developed cost impact model prediction efficiency was found to be 93.54%. The Rel. MAD of the developed cost impact model was computed to be 1.46, in other words, plus or minus 1.46; (ii) the MAPE of the developed duration impact model iii prediction efficiency is 92.94%. The Rel. MAD of the developed duration impact model computed is 0.85, in other words, plus or minus 0.85. The ANN models compared favourably with previous similar studies in terms of relative absolute deviations and mean absolute percentage errors. The ANN’s capability of learning from examples represents an innovative approach to modelling. The study concludes that the developed ANN cost and time impact prediction models have the potential to aid the construction contractor in predicting the cost outcome of a project during the construction stage, by using the significant cost and time influencing factors. The study recommends that project managers, contractors, quantity surveyors, architects, builders and engineers should place priority on the significant factors identified in this study in their project planning, monitoring and control activities. Also recommended is the conversion of the developed models into Dashboards that construction professionals could use to promptly identify the factors influencing cost and time on construction projects, and to monitor performance.
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    Modelling the relationship between project payment systems, financial management strategies and construction organisation performance in South Africa
    (2021) Omopariola, Emmanuel Dele; Windapo, Abimbola Olukemi
    The failure of construction projects to be delivered successfully – the root of poor performance in the construction industry – is attributed by scholars to the improper payment (or no payment at all) of contractors, and subsequently, of sub-contractors and suppliers. Therefore, proficient payment systems, adequate cash flow and effective financial management strategies are required for the success of construction projects. However, there is limited or no objective research that explores the impact of financial management strategies and project payment systems on construction company performance in South Africa. Also, previous research efforts have focused on various modelling approaches and their success/failure; thus, a model is yet to be developed for South Africa that will assist the construction industry practitioners in South Africa to have a reliable payment system and financial management strategy. Such a model might improve project/organisational performance. This study investigated the project payment systems and financial management strategies used by large construction organisations in achieving better performance within the business and project environment. The study further examined whether financial management strategies mediate the relationship between project payment systems and construction organisation performance. The study made use of a sequential mixed-method research approach that involves the collection of both quantitative and qualitative data to achieve the research objectives. The sample size for the study consisted of 176 contractors listed in Grades 7 to 9 on the Construction Industry Development Board (cidb) Register of Contractors. Data on the financial performance of the construction companies was obtained by gathering historical information on past projects undertaken within a five-year period (2013-2017), the payment systems used, financial management strategies adopted by the companies, and project and organisation performance data. Quantitative data analysis was carried out using both descriptive and inferential statistics. Descriptive statistics, such as percentiles and mean scores, were used to analyse the background information of the respondents and how the study population responded to the questionnaires, the typical payment systems used on construction projects and financial strategies, and the level of project and organisation performance. Structural Equation Modelling (SEM) was employed in modelling the extent to which project payment systems and financial management strategies in business and project environments influence, and are associated with, construction organisation performance. It emerged from the study that construction organisations that lack effective financial management strategies accept the use of the interim project payment system by clients on construction projects; and that financial management strategies adopted by construction companies indirectly affect their financial performance. The research also revealed that the interim payment system mediates the impact of the financial management strategies adopted, on the financial performance of construction organisations. Based on these findings, the study concluded that the failure of construction projects and organisations would be reduced through the adoption of effective financial management strategies by construction organisations and appropriate payment systems by the clients. The study highlighted channels of improving project payment systems in the construction industry, by recommending appropriate methods that suit the project environment. Also, the research proposed financial strategies and measures relating to payment and usage of the funds in the contract, so that payment and construction company performance problems in projects may be reduced. The research extends the theory on financial management strategies and its impact on financial organisational performance in the context of construction companies and the construction industry. The study contributes to the knowledge of payment systems and construction company performance, and the research and practical implications of the payment systems for the operations and performance of construction firms.
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    Modelling uncertainty of cost and time in infrastructure projects
    (2019) Moghayedi, Alireza; Windapo, Abimbola Olukemi
    The construction of infrastructure projects is characterised by cost overruns and time delays. Scholars view that the estimation approach and inappropriate tools and techniques used to forecast possible uncertainty in the construction processes are a primary cause of cost overruns and time delays on construction projects. Uncertainties encountered in the construction process are underestimated and these impact on the final cost and time of construction projects through a combination of individual construction activities. The study, therefore, examines the initial and final cost of construction activities, towards developing a hybrid tool that captures and models’ different sources of uncertainty in infrastructure projects and their effect on cost and time underestimation. The study adopted a sequential exploratory mixed method research approach that went beyond the basic mixed method approaches, employing a combination of sequential and concurrent aspects of mixed methods. Data was gathered through a series of expert panel estimation sessions, technical brainstorming of experienced professionals (with 30 years’ experience and more) in the construction of infrastructure projects, and a structured self-administered questionnaire survey distributed to project managers of South African highway projects. The developed hybrid tool models the main structures from the activity level to the entire highway project. Consequently, three identified uncertainties in the construction process of infrastructures, namely variability in the construction process, correlations between the costs, times and cost-time of construction activities and disruptive events, are modelled jointly at the construction activity level. Data obtained from both qualitative and quantitative approaches were analysed using various techniques. The probability distribution function of cost and time were modelled using the lognormal and triangular probability distributions; while Monte Carlo Simulation (MCS), Copula analysis technique, the Markov processes, and Adaptive Neuro-Fuzzy Inference System (ANFIS) analytical technique were used in modelling the variability of the cost and time activity, correlation between costs, time and cost-time activities, and to model the occurrence of disruptive events, so that the impact size of disruptive events on the cost and time of activities respectively, can be intelligently assessed. The developed uncertainty model was validated against the final cost and time of a project case study, as well as against historical data of construction cost overruns and time delays in infrastructure projects. The study found that the different uncertainties had a distinct influence on construction cost and time of different project structures. Furthermore, the comparison of the deterministic estimates with the uncertainty estimates shows that the accumulated impact of the three uncertainty sources significantly increases the construction cost and time of infrastructure projects. Based on these findings, the research concludes that the disruptive event is the main cause of cost overruns and time delays in infrastructure projects. In the scale of activity, the correlation between the costs of different activities in the same structure causes the largest increase in the cost of activity, while the correlation between the times of repeated activity in the same structure causes the largest increase in time of the activity. Furthermore, the study concludes that the improvement in the accuracy of cost and time estimation of infrastructure projects depends on a combination of probability analysis and intelligent machine learning. The contributions of the study to construction management knowledge include a clear definition of uncertainty and the sources of uncertainties in the construction of infrastructure projects; an in-depth understanding of the construction process of linear infrastructure projects; and an improvement in the quality of data used (combination of experts’ estimation and historical data) for research in the area of project performance. The developed uncertainty model based on three sources of uncertainty at the activity level provides infrastructure project planners with a hybrid dynamic tool to accurately model and predict the construction cost and time of infrastructure projects at any stage of the project. Also, the uncertainty model has three other purposes: it is the preparatory point for allocation of budget, it facilitates the update of the impact of uncertainties and evaluates the effectiveness of countermeasures to mitigate against the threat of uncertainties.
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    The nexus between building information modelling implementation strategies, adoption, and levels of construction supply chain integration in South Africa
    (2021) Olugboyega, Oluseye; Windapo, Abimbola Olukemi
    The adoption of Building Information Modelling (BIM) on construction projects is not widespread yet, because there is a growing albeit slow uptake. There is no strategically structured BIM adoption guide available on construction projects for ensuring integration and collaboration among the Building Information Modelling- Supply Chain Members (BIMSCM). Scholars adduce the lack of adoption of BIM on construction projects to the use of ineffective BIM implementation strategies. Therefore, this research investigated BIM adoption and the current dominant BIM implementation strategies used in the South African construction industry. It also examined whether BIM implementation strategies and BIM adoption on construction projects impact on the occurrence of integration and collaboration among the BIM-SCM in the South African construction industry. Using modified Implementation Process Theory, the research collected primary data using a mixed-methods research approach that involved the collection of both qualitative and quantitative data from 872 respondents randomly selected from the 1,871 BIM-based construction projects' direct participants who indicated their willingness and availability to participate in the research from the cidb databse of construction professionals in South Africa. The qualitative data collected with respect to barriers to BIM adoption and dominant BIM implementation strategies were analysed using thematic analysis. The quantitative data collected with respect to BIM adoption, barriers to BIM adoption, integration and collaboration, and BIM implementation strategies were analysed using Mean Item Score (MIS), Confirmatory Factor Analysis (CFA), and Structural Equation Modelling (SEM).The SEM method used was the Maximum Likelihood Estimation. Before modelling process, CFA was used to confirm the validity and reliability of the quantitative data using the Factor Loading, Eigenvalue, correlation coefficient, Kaiser-Meyer-Olkin (KMO) value, Bartlett's test results, and Average Variance Explained (AVE). It emerged that the possibility of getting high-value clients, quest for a competitive edge, need for technological sophistication, need to be socially acceptable to the clients, incorporation of BIM adoption into the vision of the organisations, and development of BIM capabilities as new values in their organisations are the dominant BIM implementation strategies used in the South African construction industry. The findings also revealed that the dominant BIM implementation strategies are private driven and are not bringing about an adequate reduction in the BIM adoption barriers. Investigation of the evidence of the application of BIM tools and processes with respect to the adoption of BIM on construction projects showed that fewer building information models were developed for projects, BIM performance assessment was not intensive, emphasis was not placed on the level of objects' clarity of building information models, BIM skills and competencies were insufficient, and BIM management was dis-organised. The parameter estimates from the SEM analysis of the interactions between the BIM implementation stages indicated that the success of the BIM implementation process in South Africa depends on a positive interplay between the interacting implementation stages. The parameter estimates from the SEM analysis of the interaction between the BIM implementation stages also revealed that BIM implementation strategies control the impacts of a reduction in BIM adoption barriers on the extent of BIM adoption. However, the findings revealed that the BIM implementation strategies currently in use did not possess the required forces and intensity to strengthen the positive interplay between the interacting BIM implementation stages. The study concluded that the essential BIM implementation strategies are not in use in South Africa, while the BIM implementation strategies currently in use are not appropriately and effectively employed. However, there is evidence of elementary BIM adoption on projects and low occurrence of integration and collaboration among the BIM-SCM in South Africa. The lack of adequate skills and experience of BIM management and the inadequate understanding of what BIM adoption on projects entails mean that working policies and legislation on BIM adoption are required to drive a successful BIM implementation process. This research provides new insights on the structures and stages of the BIM implementation process and postulations that will aid the comprehension of the interconnections between BIM implementation strategies and BIM adoption on construction projects in South Africa. More importantly, this research has extended the existing theories on BIM adoption and the interactions between the levels of BIM adoption on construction projects and collaboration among the BIM-SCM.